Redistribution via Taxation: The Limited Role of the Personal Income Tax in Developing Countries
Bibliographic record
Abstract
Inequality has increased in recent years in both developed and developing countries. Tax experts, like others, have focused on how taxes may reduce the inequality of income and wealth. In developed countries, the income tax, especially the personal income tax, has long been viewed as the primary instrument for redistributing income. This Article examines whether it make sense for developing countries to rely on personal income taxes to redistribute income. We think not, for three reasons. First, the personal income tax has done little, if anything, to reduce inequality in many developing countries. Second, it is not costless to pretend to have a progressive personal income tax system. Third, opportunity costs also exist from relying on taxes for redistributive purposes. If countries want to use the fiscal system to reduce poverty or reduce inequality, they need to look elsewhere. This Article begins with some initial reflections on the redistributive role of the tax system. It then considers the relative success of developed and developing countries in using tax systems to redistribute income. Finally, This Article examines some alternatives in reforming the personal income tax, as well as options available to developing countries in designing and implementing more progressive fiscal systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".